Forests provide multiple ecosystem services including water and soil protection, biodiversity conservation, carbon sequestration, and recreation, which are crucial in sustaining human health and wellbeing. Global changes represent a serious threat to Mediterranean forests, and among known impacts, there is the spread of invasive pests and pathogens, often boosted by climate change and human pressure. Remote sensing can provide support to forest health monitoring, which is crucial to contrast degradation and adopt mitigation strategies. Here, different multispectral and SAR data are used to detect the incidence of ink disease driven by Phytophthora cinnamomi in forest sites in central Italy, dominated by chestnut and cork oak respectively. Sentinel 1, Sentinel 2, and PlanetScope data, together with ground information, served as input in Random Forests to model healthy and disease classes in the two sites. The results indicate that healthy and symptomatic trees are clearly distinguished, whereas the discrimination among disease classes of different severity (moderate and severe damage) is less accurate. Crown dimension and sampled spectral regions are a critical factors in the selection of the sensor; better results are obtained for the larger chestnut crowns with Sentinel 2 data. In both sites, the red and near infra-red bands from multispectral data resulted well suited to monitor the spread of the ink disease.

每年消融期，冰面湖广泛分布于极地冰盖表面，能够存储大量冰面融水，但部分冰面湖底部破裂后会输送融水进入冰盖底部，从而影响冰盖运动与稳定性。因此，准确测算冰面湖水深信息，进而估算冰面湖体积及其动态变化，对于理解极地冰盖水文过程具有重要意义。然而，实地测量冰面湖深度难度大、成本高、覆盖范围小，通过中低空间分辨率光学遥感影像构建的冰面湖水深反演模型精度不足。该研究综合PlanetScope SuperDove光学小卫星8波段遥感影像（空间分辨率为3 m）与ICESat-2激光测高数据反演冰面湖水深。首先，通过自适应核密度估计分离并拟合湖面与湖底ICESat-2激光测高点云，进而获取冰面湖水深观测结果；其次，利用最佳波段比值分析PlanetScope影像不同波段（组合）与ICESat-2水深数据的相关关系，构建二次函数、指数函数、幂函数与对数函数4种冰面湖水深反演经验公式；最后，选择4个具有同时期PlanetScope和ICESat-2数据覆盖的冰面湖，测试冰面湖水深遥感反演的精度。结果表明PlanetScope绿光I波段是冰面湖水深反演最佳波段，单波段反射率与冰面湖水深相关性最强（R...

格陵兰冰盖的消融及其对海平面上升的贡献成为国际上研究的热点。每年消融期,格陵兰冰盖表面消融,融水会导致冰面形成冰面湖、冰面河、注水冰裂隙等形态。格陵兰冰面融水规模庞大、结构复杂、变化迅速,区域气候模型难以准确模拟冰面融水分布,中等分辨率卫星影像难以反映冰面融水的时空变化。以PlanetScope为代表的CubeSat小卫星空间分辨率高达3 m,理想情况下重访周期可达1 d,这为精细化动态监测格陵兰冰面融水提供了可能。本研究利用PlanetScope高空间分辨率小卫星遥感影像提取格陵兰冰盖西南部典型流域冰面融水遥感信息,构建了针对PlanetScope遥感影像的冰面融水深度反演公式,对比了MAR v3.11区域气候模型模拟的融水径流量与遥感反演的融水体积。结果表明:在2019年7—8月,流域内冰面融水开放水体比率先上升后下降,在7月12日达到峰值8.7%;流域内冰面融水深度介于0.2～1.5 m之间,冰面湖最深(0.9 m±0.2 m),冰面河干流次之(0.6 m±0.1 m),冰面河支流最浅(0.5 m±0.1 m);遥感观测的开放水体比率、冰面融水体积与区域气候模型MAR模拟的融水日...